• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.235-244
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• 2013

In this study, we propose a new trading strategy by using a trading volume index in KOSPI200 futures market. Many studies have been conducted with respect to the relationship between volume and price, but none of them is clearly concluded. This study analyzes the economic usefulness of investment strategy, using volume index. This analysis shows that the trading volume is a preceding index. This paper contains two objectives. The first objective is to make an index using Correlated Volume Index (CVI) and second objective is to find an appropriate timing to buy or sell the Kospi200 future index. The results of this study proved the importance of the proposed model in KOSPI200 futures market, and it will help many investors to make the right investment decision.

• Journal of the Korea Society of Computer and Information
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• v.7 no.2
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• pp.196-204
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• 2002

This paper examines the price discovery role of the KOSPI 200 futures index for its cash index. It was used the intrady data for KOSPI 200 and futures index from July 1998 to June 2001. The existing Preceding study for KOSPI 200 futures index was used the data of early market installation, but this study is distinguished to use a recent data accompanied with the great volume of transaction and various investors. We established three hypothesis to examine whether there is the price discovery role in the KOPSI 200 futures index and the characteristics of that. First, to examine whether the lead-lag relation is induced by the infrequent trading of component stocks, observations are sorted by the size of the trading volume of cash index. In a low trading volume, the long lead time is reported and the short lead time in a high volume. It is explained that the infrequent trading effect have an influence on the price discovery role. Second, to examine whether the lead-lag relation is different under bad news and good news, observations are sorted by the sign and size of cash index returns. In a bad news the long lead time is reported and the short lead time in a good news. This is explained by the restriction of"short selling" of the cash index Third, we compared estimates of the lead and lag relationships on the expiration day with those on days prior to expiration using a minute-to-minute data. The futures-to-spot lead time on the expiration day was at least as long as other days Prior to expiration, suggesting that "expiration day effects" did not demonstrate a temporal character substantially different form earlier days. Thus, while arbitrage activity may be presumed to be the greatest at expiration, such arbitrage transactions were not sufficiently strong or Pervasive to alter the empirical price relationship for the entire day. for the entire day.

• 한국산학경영학회:학술대회논문집
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• 2006.12a
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• pp.107-120
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• 2006

This thesis examines the relationship between the trading volume and price return in the korean stock Index Futures until June 2005. First, the volume of KOSPI200 futures doesn't play a primary role with the clear explanation of return model. Second, an unexpected volume shocks are negatively associated with the return in case of the KOSPI200 futures, but it is a meaningless relation in the KOSDAQ50 futures. In the case of open interest, it's difficult to find any mean in a both futures. Third, The changes in the trading volumes by foreign investors are positively associated with the return and the volatility, but individuals and domestic commercial investors are negatively associated with the return. This empirical result seems that foreign investors are initiatively trading the korean stock index futures, individuals and domestic commercial investors follow the lead made by foreign investors.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.107-134
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• 2007

This paper tests the relationship among returns, volatilities, contracts and open interests of KOSPI 200 futures markets with the various dynamic models such as granger-causality, impulse response, variance decomposition and ARMA(1, 1)-GJR-GARCH(1, 1)-M. The sample period is from July 7, 1998 to December 29, 2005. The main empirical results are as follows; First, both contract change and open interest change of KOSPI 200 futures market tend to lead the returns of that according to the results of granger-causality, impulse response and variance decomposition with VAR. These results are likely to support the KOSPI 200 futures market seems to be inefficient with rejecting the hypothesis 1. Second, we also find that the returns and volatilities of the KOSPI 200 futures market are effected by both contract change and open interest change of that due to the results of ARMA(1,1)-GJR-GARCH(1,1)-M. These results also reject the hypothesis 1 and 2 suggesting the evidences of inefficiency of the KOSPI 200 futures market. Third, the study shows the asymmetric information effects among the variables. In addition, we can find the feedback relationship between the contract change and open interest change of KOSPI 200 futures market.

• Management & Information Systems Review
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• v.32 no.4
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• pp.189-207
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• 2013

Using high-frequency data for 2 years, this study investigates intraday lead-lag relationship between stock index and stock index futures markets in Korea and China. We found that there are some differences in price discovery and volatility transmission between Korea and China after the stock index futures markets was introduced. Following Stoll-Whaley(1990) and Chan(1992), the multiple regression is estimated to examine the lead-lag patterns between the two markets by Newey-West's(1987) heteroskedasticity and autocorrelation consistent covariance matrix(HAC matrix). Empirical results of KOSPI 200 shows that the futures market leads the cash market and weak evidence that the cash market leads the futures market. New market information disseminates in the futures market before the stock market with index arbitrageurs then stepping in quickly to bring the cost-of-carry relation back into alignment. The regression tests for the conditional volatility which is estimated using EGARCH model do not show that there is a clear pattern of the futures market leading the stock market in terms of the volatility even though controlling nonsynchronous trading effects. This implies that information in price innovations that originate in the futures market is transmitted to the volatility of the cash market. Empirical results of CSI 300 shows that the cash market is found to play a more dominant role in the price discovery process after the Chinese index started a sharp decline immediately after the stock index futures were introduced. The new stock index futures markets does not function well in its price discovery performance at its infancy stage, apparently due to high barriers to entry into this emerging futures markets. Based on EGAECH model, the results uncover strong bi-directional dependence in the intraday volatility of both markets.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.751-754
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• 2020

본 논문은 지수를 추종하기 위해 유전 알고리즘에 몬테카를로 샘플링을 추가한 방법을 제안한다. 몬테카를로 샘플링을 통해 효율적으로 축소된 탐색공간을 탐험하는 유전 알고리즘은 최적의 종목들을 선택한다. 제안된 방법을 KOSPI200 지수 추종에 대하여 실험하였다. 제안된 방법이 몬테카를로 샘플링을 사용하지 않는 유전 알고리즘에 비해 지수 추종 오차가 더 낮고 더 빠르게 수렴하는 것을 보여주었다.

• The Korean Journal of Financial Management
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• v.21 no.2
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• pp.211-233
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• 2004

This purpose of paper is to propose a European option pricing formula when the rate of return follows the leptokurtic distribution instead of normal. This distribution explains well the volatility smile and furthermore the option prices calculated under the leptokurtic distribution are shown to be closer to the market prices than those of Black-Scholes model. We make an estimation of the implied volatility and kurtosis to verify the fitness of the pricing formula that we propose here.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.235-261
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• 2003

We examine the relationship between the trading activities of Korea Stock Price Index (KOSPI) 200 futures contract and its underlying stock market volatility for about six years from May 1996 when the futures contract was introduced. The trading activities of the futures contracts are proxied by the volume and open interest, which are divided into expected and unexpected portions by using the previous data. The daily, intradilay, and overnight cash volatility is estimated by the GJR-GARCH model. We find a positive contemporaneous relationship between the intradaily stock market volatility and the unexpected futures volume while the relationship between the volatility and expected futures volume is weakly negative or non-existent. We also find that the unexpected futures volume strongly causes intradaily cash volatility. On the other hand, the overnight cash volatility causes the unexpected futures volume. The impulse responses between these variables are all positive. The result implies that during a trading time futures trading tends to increase the cash volatility while the unexpected overnight changes in cash volatility tends to increase the futures trading activities. We, however, find no association between the cash volatility and futures maturities.

• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.293-308
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• 2010

In this paper, we examine the forecasting KOSPI 200 realized volatility by volatility measurements. The empirical investigation for KOSPI 200 daily returns is done during the period from 3 January 2003 to 29 June 2007. Since Korea Exchange(KRX) will launch VKOSPI futures contract in 2010, forecasting VKOSPI can be an important issue. So we analyze which volatility measurements forecast VKOSPI better. To test this hypothesis, we use 5-minute interval returns to measure realized volatilities. Also, we propose a new methodology that reflects the synchronized bidding and simultaneously takes it account the difference between overnight volatility and intra-daily volatility. The t-test and F-test show that our new realized volatility is not only different from the realized volatility by a conventional method at less than 0.01% significance level, also more stable in summary statistics. We use the correlation analysis, regression analysis, cross validation test to investigate the forecast performance. The empirical result shows that the realized volatility we propose is better than other volatilities, including historical volatility, implied volatility, and convention realized volatility, for forecasting VKOSPI. Also, the regression analysis on the predictive abilities for realized volatility, which is measured by our new methodology and conventional one, shows that VKOSPI is an efficient estimator compared to historical volatility and CRR implied volatility.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.52-56
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• 2004

The Information of classification and estimate about KOSPI200 index`s up and down in the stock market becomes an important standard of decision-making in designing portofolio in futures and option market. Because the coming trend of time series patterns, an economic indicator, is very subordinate to the most recent economic pattern, it is necessary to study the recent patterns most preferentially. This paper compares classification and estimated performance of SVM(Support Vector Machine) and Fuzzy SVM model that are getting into the spotlight in time series analyses, neural net models and various fields. Specially, it proves that Fuzzy SVM is superior by presenting the most suitable dimension to fuzzy membership function that has time series attribute in accordance with learning Data Base.